Land management trumps the effects of climate change and elevated <scp>CO</scp><sub>2</sub> on grassland functioning
Notice bibliographique
Résumé
Summary Grasslands cover ˜30% of the Earth's terrestrial surface and provide many ecosystem services. Many grasslands are heavily managed to maximize these services for human benefit, but the outcome of management is anticipated to be increasingly influenced by various aspects of climate change and elevated atmospheric CO 2 . The relative importance of global change vs. land management on grasslands is largely unknown. A meta‐analysis is used here to examine drivers at both scales primarily targeting services provided by grasslands relating to plant productivity (above‐ and below‐ground biomass) and soil processes (nutrients and soil respiration) in 38 manipulative experiments published in the last decade. We specifically target effects of (i) single and combined land management practices ( LM s), (ii) single and combined factors relating to broad‐scale climate change and elevated CO 2 , and (iii) combined management practices and changes to climate and CO 2 . Collectively, this examines the general efficacy of global change models in predicting changes to grassland functioning. We found that combinations of management practices had approximately double the explanatory power for variation in grassland services compared with individual or interactive effects of factors associated with climate change and CO 2 . These interacting management practices such as nutrient additions and defoliation predominantly influenced functions associated with productivity or biomass both below and above ground. The effects of interacting factors of climate and CO 2 influenced a wider range of ecosystem functions, but the magnitude of these effects was relatively smaller. Interactions between management practices or between climate change/ CO 2 factors always had higher explanatory power than any factor in isolation indicating that multivariate synergistic models of environmental change can better describe impacts on ecosystem function in plant communities (e.g. relative to univariate climate‐based models). Given that the magnitude and direction (positive or negative) of the interactions varied widely, this also implies that the outcomes of these multivariate interactions can vary spatially, temporally or by immediate context (e.g. management prescriptions). Synthesis . Although our work confirms how climate change and CO 2 can affect many ecosystem‐based functional attributes, it suggests that combinations of LM s remain the dominant set of factors in determining the performance of grassland plant communities. Land management may thus be critical for influencing projected responses to future climate change and elevated CO 2 in models of grassland function at least for factors relating to primary production.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».